How to make large, void free dust clusters in dusty plasma under microgravity

Collections of micrometer sized solid particles immersed in plamsa are used to mimic many systems from solid state and fluid physics, due to their strong electrostatic interaction, their large inertia, and the fact that they are large enough to be visualized with ordinary optics. On Earth, gravity restricts the so called dusty plasma systems to thin, two-dimensional layers, unless special experimental geometries are used, involving heated or cooled electrons, and/or the use of dielectric materials.In micro-gravity experiments, the formation of a dust-free void breaks the isotropy of three-dimensional dusty plasma systems. In order to do real three-dimensional experiments, this void has somehow to be closed. In this paper, we use a fully self-consistent fluid model to study the closure of a void in a micro-gravity experiment, by lowering the driving potential. The analysis goes beyond the simple description of the virtual void, which describes the formation of a void without taking the dust into account. We show that self-organization plays an important role in void formation and void closure, which also allows a reversed scheme, where a discharge is run at low driving potentials and small batches of dust are added. No hysteresis is found this way. Finally, we compare our results to recent experiments and find good agreement,but only when we do not take charge-exchange collisions into account

The effect of thermophoresis on the discharge parameters in complex plasma experiments

Thermophoresis is a tool often applied in complex plasma experiments. One of the usual stated benefits over other experimental tools is that changes induced by thermophoresis neither directly depend on, nor directly influence, the plasma parameters. From electronic data, plasma emission profiles in the sheath, and Langmuir probe data in the plasma bulk, we conclude that this assumption does not hold. An important effect on the levitation of dust particles in argon plasma is observed as well. The reason behind the changes in plasma parameters seems to be the change in neutral atom density accompanying the increased gas temperature while running at constant pressure.Comment: 14 pages, 12 figure

Determination of the levitation limits of dust particles within the sheath in complex plasma experiments

Experiments are performed in which dust particles are levitated at varying heights above the powered electrode in a RF plasma discharge by changing the discharge power. The trajectories of particles dropped from the top of the discharge chamber are used to reconstruct the vertical electric force acting on the particles. The resulting data, together with the results from a selfconsistent fluid model, are used to determine the lower levitation limit for dust particles in the discharge and the approximate height above the lower electrode where quasineutrality is attained, locating the sheath edge. These results are then compared with current sheath models. It is also shown that particles levitated within a few electron Debye lengths of the sheath edge are located outside the linearly increasing portion of the electric field

Experimental and computational characterization of a modified GEC cell for dusty plasma experiments

A self-consistent fluid model developed for simulations of micro- gravity dusty plasma experiments has for the first time been used to model asymmetric dusty plasma experiments in a modified GEC reference cell with gravity. The numerical results are directly compared with experimental data and the experimentally determined dependence of global discharge parameters on the applied driving potential and neutral gas pressure is found to be well matched by the model. The local profiles important for dust particle transport are studied and compared with experimentally determined profiles. The radial forces in the midplane are presented for the different discharge settings. The differences between the results obtained in the modified GEC cell and the results first reported for the original GEC reference cell are pointed out

Charging and coagulation of dust in protoplanetary plasma environments

Combining a particle-particle, particle-cluster and cluster-cluster agglomeration model with an aggregate charging model, the coagulation and charging of dust particles in various plasma environments relevant for proto-planetary disks have been investigated. The results show that charged aggregates tend to grow by adding small particles and clusters to larger particles and clusters, leading to greater sizes and masses as compared to neutral aggregates, for the same number of monomers in the aggregate. In addition, aggregates coagulating in a Lorentzian plasma (containing a larger fraction of high-energy plasma particles) are more massive and larger than aggregates coagulating in a Maxwellian plasma, for the same plasma densities and characteristic temperature. Comparisons of the grain structure, utilizing the compactness factor, {\phi}{\sigma}, demonstrate that a Lorentzian plasma environment results in fluffier aggregates, with small {\phi}{\sigma}, which exhibit a narrow compactness factor distribution. Neutral aggregates are more compact, with larger {\phi}{\sigma}, and exhibit a larger variation in fluffiness. Measurement of the compactness factor of large populations of aggregates is shown to provide information on the disk parameters that were present during aggregation

How companions speak on patients' behalf without undermining their autonomy: Findings from a conversation analytic study of palliative care consultations

Companions are individuals who support patients and attend health-care appointments with them. Several studies characterised companions’ participation in broad terms, glossing over the details of how they time and design their actions, and how patients and health-care practitioners (HCPs) respond to them. This article aims to examine these aspects in detail by using conversation analysis, focusing on actions whereby companions speak on patients’ behalf—mentioning delicate aspects of patients’ experience (specifically, by alluding to patients’ thoughts or feelings about dying). Some studies suggested that these actions undermine patients’ autonomy. By contrast, through examination of palliative care consultations in a UK hospice, we found that these interventions are warranted by contextual circumstances: they are either invited by patients or HCPs (through questions or gaze) or volunteered to help with the progression of an activity (e.g. when a patient does not answer an HCP’s question). Additionally, all parties collaborate in constructing these companion interventions as temporary departures from an otherwise prevailing normative orientation to patients’ right to speak for themselves. The study contributes to the sociology of health and illness by characterising how companions contribute to the ways in which participants coordinate their relative rights and responsibilities, and ultimately their relationships, within health-care interactions

Metabolic and hormonal studies of Type 1 (insulin-dependent) diabetic patients after successful pancreas and kidney transplantation

Long-term normalization of glucose metabolism is necessary to prevent or ameliorate diabetic complications. Although pancreatic grafting is able to restore normal blood glucose and glycated haemoglobin, the degree of normalization of the deranged diabetic metabolism after pancreas transplantation is still questionable. Consequently glucose, insulin, C-peptide, glucagon, and pancreatic polypeptide responses to oral glucose and i.v. arginine were measured in 36 Type 1 (insulin-dependent) diabetic recipients of pancreas and kidney allografts and compared to ten healthy control subjects. Despite normal HbA1 (7.2±0.2%; normal <8%) glucose disposal was normal only in 44% and impaired in 56% of the graft recipients. Normalization of glucose tolerance was achieved at the expense of hyperinsulinaemia in 52% of the subjects. C-peptide and glucagon were normal, while pancreatic polypeptide was significantly higher in the graft recipients. Intravenous glucose tolerance (n=21) was normal in 67% and borderline in 23%. Biphasic insulin release was seen in patients with normal glucose tolerance. Glucose tolerance did not deteriorate up to 7 years post-transplant. In addition, stress hormone release (cortisol, growth hormone, prolactin, glucagon, catecholamines) to insulin-induced hypoglycaemia was examined in 20 graft recipients and compared to eight healthy subjects. Reduced blood glucose decline indicates insulin resistance, but glucose recovery was normal, despite markedly reduced catecholamine and glucagon release. These data demonstrate the effectiveness of pancreatic grafting in normalizing glucose metabolism, although hyperinsulinaemia and deranged counterregulatory hormone response are observed frequently

Joint Learning of Intrinsic Images and Semantic Segmentation

Semantic segmentation of outdoor scenes is problematic when there are variations in imaging conditions. It is known that albedo (reflectance) is invariant to all kinds of illumination effects. Thus, using reflectance images for semantic segmentation task can be favorable. Additionally, not only segmentation may benefit from reflectance, but also segmentation may be useful for reflectance computation. Therefore, in this paper, the tasks of semantic segmentation and intrinsic image decomposition are considered as a combined process by exploring their mutual relationship in a joint fashion. To that end, we propose a supervised end-to-end CNN architecture to jointly learn intrinsic image decomposition and semantic segmentation. We analyze the gains of addressing those two problems jointly. Moreover, new cascade CNN architectures for intrinsic-for-segmentation and segmentation-for-intrinsic are proposed as single tasks. Furthermore, a dataset of 35K synthetic images of natural environments is created with corresponding albedo and shading (intrinsics), as well as semantic labels (segmentation) assigned to each object/scene. The experiments show that joint learning of intrinsic image decomposition and semantic segmentation is beneficial for both tasks for natural scenes. Dataset and models are available at: https://ivi.fnwi.uva.nl/cv/intrinsegComment: ECCV 201